Stand-alone wearable system for ubiquitous real-time monitoring of muscle activation potentials

Wearable technology is attracting most attention in healthcare for the acquisition of physiological signals. We propose a stand-alone wearable surface ElectroMyoGraphy (sEMG) system for monitoring the muscle activity in real time. With respect to other wearable sEMG devices, the proposed system includes circuits for detecting the muscle activation potentials and it embeds the complete real-time data processing, without using any external device. The system is optimized with respect to power consumption, with a measured battery life that allows for monitoring the activity during the day. Thanks to its compactness and energy autonomy, it can be used outdoor and it provides a pathway to valuable diagnostic data sets for patients during their own day-life. Our system has performances that are comparable to state-of-art wired equipment in the detection of muscle contractions with the advantage of being wearable, compact, and ubiquitous

Myoelectric Control Systems for Hand Rehabilitation Device: A Review

One of the challenges of the hand rehabilitation device is to create a smooth interaction between the device and user. The smooth interaction can be achieved by considering myoelectric signal generated by human's muscle. Therefore, the so-called myoelectric control system (MCS) has been developed since the 1940s. Various MCS's has been proposed, developed, tested, and implemented in various hand rehabilitation devices for different purposes. This article presents a review of MCS in the existing hand rehabilitation devices. The MCS can be grouped into main groups, the non-pattern recognition and pattern recognition ones. In term of implementation, it can be classified as MCS for prosthetic and exoskeleton hand. Main challenges for MCS today is the robustness issue that hampers the implementation of MCS on the clinical application

Using High Density EMG to Proportionally Control 3D Model of Human Hand

Control of human hand using surface electromyography (EMG) is already established in various mechanisms, but proportionally controlling magnitudes degrees of freedom (DOF) of humanoid hand model is still highly developed in recent years. This paper proposes another method to achieve a proportional estimation and control of human’s hand multiple DOFs. Gestures in the form of American Sign Language (ABCDFIKLOW) were chosen as the targets, of which ten alphabetical gestures were specifically used following their clarity on its 3D model. Then the dataset of the movements gestures was simultaneously recorded using High-density electromyography (HD-EMG) and motion capture system. Sensor placements were on intrinsic - extrinsic muscles for HD-EMG and finger joints for the motion capture system. To derive the proportional control in time series between both datasets (HD-EMG and kinematics data), neural network (NN) and k-Nearest Neighbour were used. The models produced around 70-95 % (R index) accuracy for the eleven DOFs in four healthy subjects’ hand. kNN’s performance was better than NN, even if the input features were reduced either using manual selections or principal component analysis (PCA). The time series controls could also identify most sign language gestures (9 of 10), with difficulty was given on O gesture. The false interpretation was because of nearly identical muscle’s EMG and kinematics data between O and C. This paper intends to extend its conference version [1] by adding more in-depth Results and Discussion along making other sections more comprehensive

Regressing Grasping Using Force Myography: An Exploratory Study

Background: Partial hand amputation forms more than 90% of all upper limb amputations. This amputation has a notable efect on the amputee’s life. To improve the quality of life for partial hand amputees diferent prosthesis options, including externallypowered prosthesis, have been investigated. The focus of this work is to explore force myography (FMG) as a technique for regressing grasping movement accompanied by wrist position variations. This study can lay the groundwork for a future investigation of FMG as a technique for controlling externally-powered prostheses continuously. Methods: Ten able-bodied participants performed three hand movements while their wrist was fxed in one of six predefned positions. The angle between Thumb and Index fnger (θTI), and Thumb and Middle fnger (θTM) were calculated as measures of grasping movements. Two approaches were examined for estimating each angle: (i) one regression model, trained on data from all wrist positions and hand movements; (ii) a classifer that identifed the wrist position followed by a separate regression model for each wrist position. The possibility of training the system using a limited number of wrist positions and testing it on all positions was also investigated. Results: The frst approach had a correlation of determination (R2) of 0.871 for θTI and R2 θTM = 0.941. Using the second approach R2 θTI = 0.874 and R2 θTM = 0.942 were obtained. The frst approach is over two times faster than the second approach while having similar performance; thus the frst approach was selected to investigate the efect of the wrist position variations. Training with 6 or 5 wrist positions yielded results which were not statistically signifcant. A statistically signifcant decrease in performance resulted when less than fve wrist positions were used for training. Conclusions: The results indicate the potential of FMG to regress grasping movement, accompanied by wrist position variations, with a regression model for each angle. Also, it is necessary to include more than one wrist position in the training phase

Explication of Extrinsic Forearm Muscles On the Classification of Thumb Position Using High-Density Surface Electromyogram

Muscles for hand functions and movements play a major role in basic daily activities such as writing and lifting objects. The main digit of the finger in differentiating the hand gesture is the thumb and its main muscles are intrinsic muscles. However, for transradial amputees, despite the loss of access to the intrinsic muscles, any information from the extrinsic muscles would be paramount and non-negotiable in creating a perfect hand prosthesis. As such, the research is dedicated to studying the relationship between extrinsic muscles located at the human’s forearm to characterize the actual thumb attitudes. A 64-channel HD-sEMG recording device together with a thumb force measuring platform was utilized to collect the required signals from 17 participants at several thumb angle positions namely zero-degrees, thirty-degree, sixty-degrees, and ninety-degree. For each position, the participants were required to place their thumbs on top of a load cell at relaxing (no force at all) and contact (30% of their individual Maximum Voluntary Contraction or known as MVC) conditions repetitively by following a designated trajectory. Feature extraction was performed by calculating the Root Mean Square (RMS) values of the HD-sEMG data collected from each channel. Six different classifiers have been used to classify the relationship between the forearm HD-sEMG and the corresponding thumb positions. As a result, LazyIBK obtained the highest correctly classified instances with 81.05%. The finding is significant in developing a dedicated control framework for a prosthetic hand for tansradial amputees that can operate as closely as normal

Explication of Extrinsic Forearm Muscles On the Classification of Thumb Position Using High-Density Surface Electromyogram

Muscles for hand functions and movements play a major role in basic daily activities such as writing and lifting objects. The main digit of the finger in differentiating the hand gesture is the thumb and its main muscles are intrinsic muscles. However, for transradial amputees, despite the loss of access to the intrinsic muscles, any information from the extrinsic muscles would be paramount and non-negotiable in creating a perfect hand prosthesis. As such, the research is dedicated to studying the relationship between extrinsic muscles located at the human’s forearm to characterize the actual thumb attitudes. A 64-channel HD-sEMG recording device together with a thumb force measuring platform was utilized to collect the required signals from 17 participants at several thumb angle positions namely zero-degrees, thirty-degree, sixty-degrees, and ninety-degree. For each position, the participants were required to place their thumbs on top of a load cell at relaxing (no force at all) and contact (30% of their individual Maximum Voluntary Contraction or known as MVC) conditions repetitively by following a designated trajectory. Feature extraction was performed by calculating the Root Mean Square (RMS) values of the HD-sEMG data collected from each channel. Six different classifiers have been used to classify the relationship between the forearm HD-sEMG and the corresponding thumb positions. As a result, LazyIBK obtained the highest correctly classified instances with 81.05%. The finding is significant in developing a dedicated control framework for a prosthetic hand for tansradial amputees that can operate as closely as normal

Causal evidence that intrinsic beta frequency is relevant for enhanced signal propagation in the motor system as shown through rhythmic TMS

Correlative evidence provides support for the idea that brain oscillations underpin neural computations. Recent work using rhythmic stimulation techniques in humans provide causal evidence but the interactions of these external signals with intrinsic rhythmicity remain unclear. Here, we show that sensorimotor cortex precisely follows externally applied rhythmic TMS (rTMS) stimulation in the beta-band but that the elicited responses are strongest at the intrinsic individual beta-peak-frequency. While these entrainment effects are of short duration, even subthreshold rTMS pulses propagate through the network and elicit significant cortico-spinal coupling, particularly when stimulated at the individual beta-frequency. Our results show that externally enforced rhythmicity interacts with intrinsic brain rhythms such that the individual peak frequency determines the effect of rTMS. The observed downstream spinal effect at the resonance frequency provides evidence for the causal role of brain rhythms for signal propagation

Madala maksumusega elektromüograafide rakendatavus ergonoomikalises hindamises

A thesis for applying for the degree of Doctor of Philosophy in Engineering Sciences.Every year a considerable amount of gross domestic product in several countries is lost due to work-related musculoskeletal disorders (WMSDs). Thus, one of the goals of ergonomics is to prevent WMSDs. A body of knowledge required to prevent WMSDs has existed for decades; however, the exploitation of this knowledge is hindered by the shortcomings in the risk assessment methods. As a rule, objective methods should be preferred to subjective methods, though often access to objective methods is restricted by the cost of the apparatus. The potential to make one of such devices more accessible by reducing the costs was investigated in the thesis. The thesis focused on the electromyograph – a device to study and monitor the electrical activity produced by skeletal muscles. Nowadays one can assemble an electromyograph from low-cost semi-universal components; however, the functionality and usability of such a device is unknown. At first the technical characteristics of components that can be used to assemble an electromyograph were evaluated. Then the electromyographs were assembled and tested in the laboratory and in the field. The results showed that the low-cost electromyographs may be partially utilised in ergonomic risk assessment; however, the use of such equipment in comparison to commercial high-cost apparatus increases the demands on user knowledge, skills and time expenditure. On the other hand, the functionality of the do-it-yourself electromyograph may exceed the commercial device.Tööga seotud luu- ja lihaskonna ülekoormushaiguste tõttu kaotavad riigid igal aastal märkimisväärse osa sisemajanduse kogutoodangust. Seetõttu on üheks ergonoomika eesmärgiks luu- ja lihaskonna ülekoormushaiguste ennetamine. Teadmised töötaja ülekoormuse ennetamiseks on olemas juba aastakümneid. Paraku takistavad teadmiste tõhusat rakendamist puudused riskihindamise meetodites. Riskide hindamisel tuleb subjektiivsetele meetoditele eelistada objektiivseid meetodeid, kuid sageli piirab objektiivsete meetodite kasutamist mõõteseadmete maksumus. Doktoritöös uuriti ühe sellist liiki mõõteseadme, lihaste elektrilise aktiivsuse uurimiseks mõeldud seireseadme ehk elektrimüograafi kättesaadavuse ja rakendamise suurendamise võimalust seadme maksumuse vähendamisega. Nüüdisajal on võimalus elektromüograafe kokku panna madala maksumusega ja pool-universaalsetest komponentidest. Samas pole selge, milline on sellisel viisil valmistatud elektromüograafi funktsionaalsus ja kasutatavus. Doktoritöös hinnati esmalt elektromüograafi madala maksumusega komponentide tehnilisi omadusi ning seejärel katsetati koostatud elektromüograafe laboris ja töökeskkonnas. Doktoritöö andis kinnitust, et madala maksumusega elektromüograafe on võimalik riskihindamisel osaliselt rakendada, kuid selliste seadmete kasutamine eeldab riskihindajalt põhjalikumaid teadmisi ja oskusi ning suuremat ajakulu kui kallite kommertsseadmete kasutamine. Samas võib spetsialisti kokkupandud elektromüograafi funktsionaalsus kommertsseadmeid ületada.Publication of this thesis is supported by the Estonian University of Life Sciences. This research was supported by European Regional Development Fund’s Doctoral Studies and Internationalisation Programme DoR